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Customer Segmentation Toolkit

$39

RFM analysis, customer lifetime value calculation, churn prediction models, and personalized campaign targeting scripts.

📁 7 files🏷 v1.0.0
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📁 File Structure 7 files

customer-segmentation-toolkit/ ├── LICENSE ├── README.md ├── config.example.yaml ├── pyproject.toml └── src/ └── customer_segmentation_toolkit/ ├── __init__.py ├── core.py └── utils.py

📖 Documentation Preview README excerpt

Customer Segmentation Toolkit

RFM analysis, customer lifetime value calculation, churn prediction models, and personalized campaign targeting scripts.

Contents

  • config.example.yaml
  • pyproject.toml
  • src/customer_segmentation_toolkit/__init__.py
  • src/customer_segmentation_toolkit/core.py
  • src/customer_segmentation_toolkit/utils.py

Quick Start

1. Extract the ZIP archive

2. Review the README and documentation

3. Customize configuration files for your environment

4. Follow the setup guide for your specific use case

Requirements

  • Python 3.10+ (for Python scripts)
  • Relevant CLI tools for your platform
  • Access to your target environment

License

MIT License — see LICENSE file.

Support

Questions or issues? Email megafolder122122@hotmail.com

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Part of [Retail Ecommerce](https://inity13.github.io/retail-automation-pro/)

📄 Code Sample .py preview

src/customer_segmentation_toolkit/core.py """ Customer Segmentation Toolkit — Core Module Production-ready implementation. """ from typing import Any, Dict, List, Optional from dataclasses import dataclass, field from datetime import datetime import json import logging logger = logging.getLogger(__name__) @dataclass class Config: """Configuration for Customer Segmentation Toolkit.""" name: str = "customer-segmentation-toolkit" version: str = "1.0.0" debug: bool = False log_level: str = "INFO" output_dir: str = "./output" settings: Dict[str, Any] = field(default_factory=dict) @classmethod def from_file(cls, path: str) -> "Config": with open(path) as f: data = json.load(f) return cls(**data) def to_dict(self) -> Dict[str, Any]: return { "name": self.name, "version": self.version, "debug": self.debug, "log_level": self.log_level, "output_dir": self.output_dir, "settings": self.settings, } class CustomerSegmentationToolkit: """Main class for Customer Segmentation Toolkit.""" def __init__(self, config: Optional[Config] = None): self.config = config or Config() self._setup_logging() self._results: List[Dict[str, Any]] = [] logger.info(f"Initialized {self.config.name} v{self.config.version}") def _setup_logging(self): # ... 40 more lines ...